Objective: To identify common and rare genetic variants that increase the risk of schizophrenia (SCZ), and to study their impact on illness risk as well as measures of morbidity in large samples. Background: Schizophrenia is a major cause of disability amongst US veterans as well as worldwide, with an annual public health burden of more than $60 billion. Recent studies have strongly supported the impact of both common and rare variants on illness risk. However, the known genetic risk factors for the illness still comprise a small portion of the overall heritability, which is about 80%. These variants are more likely to occur in non-coding than coding regions of the genome. For this and other reasons, whole-genome sequencing (WGS) has become the method of choice to identify genetic risk variants for SCZ and other common, complex disorders. Although prohibitively expensive only a few years ago, it is now feasible to carry out WGS in large numbers affordably. In the last grant period, we successfully conducted WGS in 20 families segregating either SCZ or bipolar disorder from the geographically isolated Portuguese Islands of the Azores and Madeira. We have shown that rare variants segregating with illness in these families preferentially cluster in regions previously implicated by GWAS. Genetic risk factors are likely to be easier to identify in more isolated populations because of their greater homogeneity, and consequently fewer genetic inputs to disease. Proposed Methods: We plan to enlarge our current sample of multiplex Azorean families segregating SCZ by ascertaining and collecting new families in the Azores as well as following up previously studied families to identify individuals who have entered the age of risk for SCZ. These families will undergo WGS using the Illumina HiSeqX to identify common and rare single nucleotide variants and structural variants associated with illness. These families will be sequenced alongside the Genomic Psychiatry Cohort (GPC), a large US sample of SCZ and bipolar cases and controls (10,000 cases and 10,000 controls), and variant calling will be done with this much larger sample to increase accuracy. Furthermore, we will be able to use the GPC as a replication sample in a two-stage design, which we demonstrate has greater power than a one-stage design. We will also examine genetic influences on phenotypes relevant to Precision Medicine, such as symptomatic dimensions and outcome.